23857 - Applied Geostatistic

Learning outcomes

The mission of the course is to provide basic training for processing the Regionalized Variables, that is, most of quantities which characterize georesources from the chemical, physical and geometrical point of view (i.e. contents and grades of elements and substances in soils, waters and air; porosity, permeability, deepness, thickness of geological formations; colour of ornamental stone slabs).

The theoretical tools for studying many of the problems linked to georesources are provided (i.e. selection of polluted/mineralized areas; mapping of space-time variables distributions; sampling optimization)

Learning outcomes refer to the probabilistic characterization of space-time Regionalized Variables (Random Functions, Variograms, spatial Covariances) and a few operational tools such as the optimal estimators (kriging). Namely, the Linear Geostatistic, stationary and non-stationary, monovariate and multivariate, are focused upon.

Course contents

LESSONS
·      Introduction & problems

- Monovariate Stationary Geostatistics
·      Probability Rudiments, Random Variables, Probability Laws, Moments
·      Regionalized Variables, Random Functions and Autocorrelation Functions
·      Experimental Variograms and Variogram Modelling
·      Regularization
·      Dispersion Variance and Selectivity
·      Linear Estimation: Ordinary Kriging of points and domains

- Monovariate Non Stationary Geostatistics
·      Non-stationary Random Functions, the drift, the Universal Kriging
·      Introduction to Intrinsic Random Functions of k-order and IRF-k Kriging

- Multivariate Geostatistics
·      Multivariable Analysis, Cross-Covariances and Cross-Variograms
·      Cokriging
·      Spatial Components, Collocated Cokriging, External Drift

- Selection
·      Selection
·      Sampling
·      Case Studies

PRACTICAL EXERCISES
- Theory Application by existing software and by programming algorithms through  macros
·      Basic statistics and probability laws, by EXCEL.
·      Experimental variograms and variogram modelling , by EXCEL (Macro), FAIPACK & MULTIGEO.
·      Regularization. Regularized Variograms.
·      Ordinary Kriging, by EXCEL (Macro).
·      Non Stationary Random Functions, by FAIPACK
·      Cross Variograms and Covariances, by EXCEL & MULTIGEO.
·      Cokriging, by MULTIGEO
·      Selection, by EXCEL
·      Sampling Optimization, by EXCEL

- Intermediate tests & correction

Readings/Bibliography

COURSE's TEXTS

• Bruno, Roberto                CLASS NOTES (power-point)
• Raspa, G. & Bruno, R.    GEOSTATISTICS NOTES (pdf)

BIBLIOGRAPHY

• Bruno, R. and Raspa, G. (1994) - La pratica della geostatistica lineare: il trattamento dei dati spaziali - Edizioni Angelo Guerini ed Associati S.r.l., 170 pp.

• Chiles, J.P. & Delfiner, Pierre (1999) - Geostatistics - Wiley Series in Probability and Statistics, - John Wiley and sons, Inc., 687 pp.

Teaching methods

Each lecture introduces a real problem case linked to georesources. The problems to be solved are discussed and the approach necessary for solving the problem at hand is identified. Afterwards the specific theory for the solution of the problem case is developed.

Lectures are coupled with practical exercises aimed to put into practice the introduced concepts and theoretical models. Practical exercises are given at the Didaptic-Informatic Laboratory, by using available software and by developing specific macros for specific computations.

Assessment methods

Two assessment methods are provided , one for students attending the classes, another for students who cannot attend.

-          Attending students

During the course, two intermediate tests are arranged, one on the Stationary Monovariate Geostatistics, approximately at the middle of the course, and another on Multivariate and Non Stationary Geostatistics approximately a week before the end of the course.

Finally, the student must write a short dissertation, consisting of a real-case study chosen by the students themselves, based on the collected related data. The final examination is based on the short dissertation. Final grades are obtained by a weighted mean among intermediate tests and short dissertation results.

 

-          Students who cannot attend

The assessment is made by a short dissertation putting into practice the theory and consisting of a real case study chosen by students themselves, based on the collected related data . During the dissertation, theoretical command of the discipline is assessed.

N.B. - The short dissertation can be developed in contact with the lecturer who guides the analysis and useful computations.

Teaching tools

Lectures are given by projecting power point files supported by notes on the black/white board.
The practical exercises are given at the Didaptic-Informatic Laboratory.

During practical exercises, besides the Microsoft Office programs, geostatistical freeware software is used. In particular, the following programs are used:

• FAIPACK
• MULTIGEO
• EXCEL

Links to further information

http://serwebdicma.ing.unibo.it/labingmin/

Office hours

See the website of Roberto Bruno